The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
is a leading international conference in the areas of knowledge discovery
and data mining (KDD). It provides an international forum for researchers
and industry practitioners to share their new ideas, original research
results and practical development experiences from all KDD related areas,
including data mining, data warehousing, machine learning, artificial
intelligence, databases, statistics, knowledge engineering, visualization,
decision-making systems and the emerging applications.

Topics

The topics of relevance for the conference papers include but not limited
to the following:

The submitted paper should adhere to the double-blind review policy.
All papers will be double-blind reviewed by the Program Committee on
the basis of technical quality, relevance to data mining, originality,
significance, and clarity. All paper submissions will be handled
electronically. Detailed instructions are provided on the conference
home page. Papers that do not comply with the Submission Guidelines
will be rejected without review.

Each submitted paper should include an abstract up to 200 words and
be not longer than 12 single-spaced pages with 10pt font size.
Authors are strongly encouraged to use Springer LNCS/LNAI manuscript
submission guidelines (available at http://www.springer.de/comp/lncs/authors.html)
for their initial submissions. All papers must be submitted
electronically through the paper submission system in PDF format only.

The submitted papers must not be previously published anywhere, and
must not be under consideration by any other conferences or journal
during the PAKDD review process. Submitting a paper to the conference
means that if the paper were accepted, at least one author will attend
the conference to present the paper. For no-show authors, their
affiliations will receive a notification. The program committee chairs
are not allowed to submit papers to the conference for a fair review
process.

The conference will confer several awards including Best Paper Awards,
Best student Paper Awards and Best Application Paper Awards from the
submissions.

The proceedings of the conference will be published by Springer
as a volume of the LNAI series and selected excellent papers will
be invited for publications in special issues of high-quality journals
including Knowledge and Information Systems (KAIS) and
International Journal of Machine Learning and Cybernetics (IJMLC).

Especially, for PAKDD 2016, the Steering Committee will sponsor two
sets of travel awards: Student Travel Awards and Early Career Researcher
Travel Awards. We have allocated $4,000 USD for each and suggest that
10 awards be presented for each at $400 USD each to contribute towards
travel.

Program Committee Co-chairs
James Bailey, The University of Melbourne, Australia
Latifur Khan, University of Texas at Dallas, USA
Takashi Washio, Institute of Scientific and Industrial Research, Osaka University, Japan

Workshop Co-chairs:
Huiping Cao, New Mexico State University
Jinyan Li, University of Technology Sydney

Local Arrangement Co-chairs
Yun Sing Koh, University of Auckland, New Zealand
Ranjini Swaminathan, University of Auckland, New Zealand

Proceedings Chair
Ruili Wang, Massey University, New Zealand

Contest Chair
Muhammad Asif Naeem, AUT University, New Zealand

Publicity and Website Chair
David Tse Jung Huang, University of Auckland, New Zealand

Registration Chair
Ranjini Swaminathan, University of Auckland, New Zealand

Further Information
For further information, please contact the Program Committee Chairs by pakdd2016@gmail.com